Product Images Good Sense Nicotine

View Photos of Packaging, Labels & Appearance

Product Label Images

The following 11 images provide visual information about the product associated with Good Sense Nicotine NDC 0113-0854 by L. Perrigo Company, such as packaging, labeling, and the appearance of the drug itself. This resource could be helpful for medical professionals, pharmacists, and patients seeking to verify medication information and ensure they have the correct product.

decide - image 01

decide - image 01

expect - image 02

expect - image 02

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relapse - image 03

good_luck - image 04

good_luck - image 04

dosage - image 05

dosage - image 05

Recommended dosage schedule for Nicotine Polacrilex Gum is provided in three steps where the first step suggests using it after 1-2 hours, the second step suggests using it after 2-4 hours, and the third step suggests using it after 4-8 hours. The product is made in Denmark. The last line of the text is not readable and is considered non-English characters.*

wallet - image 06

wallet - image 06

This text provides a list of emergency contact numbers for health-related organizations, including the American Lung Association, American Cancer Society, and American Heart Association. It appears to be a wallet-sized card that can be easily carried around for quick reference.*

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wallet - image 07

logo - image 08

logo - image 08

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upc - image 09

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stickers - image 10

This appears to be instructions for a nicotine replacement therapy (possibly gum or lozenges) program designed to help someone quit smoking. The program involves gradually reducing the frequency of nicotine use over several weeks, starting with taking 1 piece every 1-2 hours (Step 1), then transitioning to 1 piece every 2-4 hours (Step 2), and eventually only taking 1 piece every 4-8 hours (Step 3) by the tenth week. The dates at each step indicate the recommended timeframe for when to transition to the next step or stop using the nicotine replacement therapy altogether.*

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image 11

* The product label images have been analyzed using a combination of traditional computing and machine learning techniques. It should be noted that the descriptions provided may not be entirely accurate as they are experimental in nature. Use the information in this page at your own discretion and risk.